Some imaging devices include passive auto-focus techniques with object recognition logic to detect an object of interest as the focal point instead of using a static or user-selected focus areas. Object detection in digital imaging devices is computationally intensive and processing speeds are slow compared to processing requirements. Further, if the detection logic is too slow, the objects in the image may move to different locations before results for the previous scene are available.
During detection, the field of view is divided into patches and objects are typically searched for by examining every individual patch at a particular size in an image, left to right, top to bottom. The patch size is then increased or decreased and the entire image is traversed again, repeating however many times necessary until all possible patches have been examined. Patch sizes range from small (for distances far from the camera lens) to large (for distances close to the camera lens). When the size of the patch being evaluated is large, the number of patches that need to be evaluated to traverse the image is small. When the size of the patch being evaluated is small, the number of patches that need to be evaluated to traverse the image is large. Because of the difference in patch sizes, and hence the difference in the number of patches that need to be evaluated, it takes much more time to traverse an image when evaluating small patch sizes than it does to traverse the same image when evaluating large patch sizes. Current solutions have no preference in finding either small objects or large objects. The disadvantage of this lack of preference means that it always takes roughly the same amount of time to run the entire object detection.